Architect - Conversational AI

Roles and Responsibilities:

1. Technical Project Delivery:

a. Own the complete SDLC of our product(s) by managing the solutioning, engineering, testing, release and maintenance

b. Lead engagements with multiple work-streams; prepare project plans and manage deliverables

c. Guide and help team members to debug and solve technical problems

d. Review and perform code walkthrough and quality reviews

2. Client Management:

a. Managing customer communication & relationships

b. Guide the client on technology evaluation, technical thought leadership and direction for Conversational AI projects

c. Constantly sync with the product & Business team to align on business priorities, and plan for long term and

short-term architecture goals

d. Showcase thought leadership on technology roadmaps, agile development methodologies and best practices

e. Challenge and inspire customers and peers to solve difficult problems with ambitious and novel solutions

3. Team management:

a. Work with the team to identify and qualify business opportunities. Identify key customer technical objections and

develop a strategy to resolve technical blockers

b. Ensure proper skill development of team members

4. Travel to customer sites, conferences, and other related events as required

Required Skills:

1. Experience with

a. AI Bot platforms, such as DialogFlow/API.AI, Cloud ML, Microsoft Bot Framework and Azure Cognitive Services,

Amazon Lex, IBM Watson, Wit.ai, Salesforce Einstein, Rasa etc. (as a Project Manager/Analyst/Consultant)

OR

b. Software and Product Development on languages like NodeJs, Python etc.

2. Excellent communication, articulation, abstraction, analytical and presentation skills

3. Ability to work with minimal supervision in a dynamic and time sensitive work environment

4. Team management experience is must

5. Excellent aptitude in business analysis and awareness of quantitative analysis techniques

6. Knowledge of one of NodeJS or Python is a must

7. Understanding of Natural Language Processing (NLP) and supervised Machine Learning

(ML) concepts (such as vectorization, N-gram, classification, clustering, overtraining etc.)

8. Experience with deploying machine learning algorithms as REST API based services

9. Experience working with scalable, high-performance systems

10. Experience in architecting solutions and integrations with multiple technologies and Systems.

Nice to have skills:

1. Strong understanding of the NLP space (natural language understanding, sentiment analysis, personality insight etc.),

conversational interfaces, and leveraging existing services and libraries (integration, configuration, training, continuous

learning)

2. Well versed with voiced based processing (text to speech, speech to text)

3. Experiences with Databases – relational and non-relational

4. Experience in the Cloud deployments on GCP, AWS or Azure